Post by Ekaterina Miliutina

I am honored to have contributed as a co-author to our recently published paper: "RS-WaterQuality Mapper: An Open-Source Water Quality Mapping Plugin for Remote Sensing Applications" This study presents RS-WaterQuality Mapper, an open-source plugin developed for the QGIS platform to support remote sensing-based water quality monitoring. The plugin provides an integrated workflow for building, validating, and applying water quality models using multispectral imagery and in situ measurements. RS-WaterQuality Mapper incorporates machine learning approaches, including Random Forest regression, and enables users to estimate key water quality parameters such as chlorophyll-a, turbidity, and colored dissolved organic matter (CDOM/fDOM) from remotely sensed data. By bringing these capabilities into a user-friendly QGIS environment, the plugin helps streamline water quality mapping workflows for researchers, students, and environmental practitioners. It is exciting to see this work published and contribute to the development of open-source tools that support more accessible and reproducible environmental monitoring. 📖 Publication: https://lnkd.in/ewJCHDT3 #QGIS #RemoteSensing #WaterQuality #GIS #MachineLearning #EnvironmentalMonitoring #OpenSource #EarthObservation #Research